code: def hybrid_forward(self, F, inputs):
      mean_out = F.mean(data=inputs, axis=self.axis)
      max_out = F.max(data=inputs, axis=self.axis)
      outputs = F.concat(mean_out, max_out, dim=1)
      if self.dropout:
          outputs = F.Dropout(data=outputs, p=self.dropout)
      # outputs = F.LayerNorm(outputs)
      return outputs
  
file_path: analytics-zoo/pyzoo/zoo/models/recommendation/txt.py
imports: from mxnet import gluon
  from gluonnlp.model.transformer import TransformerEncoder, TransformerEncoderCell
label_desc: Use image node_id 2 for calling the MeanMaxPooling obj's underlying member method code with example usage: obj.hybrid_forward(F, inputs) and returns: outputs